Add explain analysis workflow and UI

backend/tests/test_news_enricher.py

@@ -0,0 +1,174 @@
+# -*- coding: utf-8 -*-
+
+from backend.enrich import news_enricher
+
+
+def test_classify_news_row_falls_back_to_local_rules(monkeypatch):
+    monkeypatch.setattr(news_enricher, "analyze_news_row_with_llm", lambda row: None)
+    result = news_enricher.classify_news_row(
+        {
+            "title": "Apple shares drop after weak guidance",
+            "summary": "Investors reacted negatively to softer-than-expected outlook.",
+        }
+    )
+    assert result["analysis_source"] == "local"
+    assert result["sentiment"] == "negative"
+    assert result["summary"]
+
+
+def test_classify_news_row_prefers_llm_when_available(monkeypatch):
+    monkeypatch.setattr(
+        news_enricher,
+        "analyze_news_row_with_llm",
+        lambda row: {
+            "relevance": "high",
+            "sentiment": "positive",
+            "key_discussion": "Demand resilience",
+            "summary": "LLM summary",
+            "reason_growth": "Orders remain strong",
+            "reason_decrease": "",
+            "raw_json": {"provider": "llm"},
+        },
+    )
+    result = news_enricher.classify_news_row(
+        {
+            "title": "Apple expands AI features",
+            "summary": "New devices and software updates were announced.",
+        }
+    )
+    assert result["analysis_source"] == "llm"
+    assert result["sentiment"] == "positive"
+    assert result["summary"] == "LLM summary"
+
+
+def test_build_analysis_rows_prefers_batch_llm_and_dedupes(monkeypatch):
+    monkeypatch.setattr(news_enricher, "llm_enrichment_enabled", lambda: True)
+    monkeypatch.setattr(news_enricher, "get_env_int", lambda key, default=0: 8)
+    monkeypatch.setattr(
+        news_enricher,
+        "analyze_news_rows_with_llm",
+        lambda rows: {
+            "news-1": {
+                "relevance": "high",
+                "sentiment": "positive",
+                "key_discussion": "Batch result",
+                "summary": "Batch summary",
+                "reason_growth": "Growth",
+                "reason_decrease": "",
+                "raw_json": {"provider": "batch"},
+            }
+        },
+    )
+    monkeypatch.setattr(news_enricher, "analyze_news_row_with_llm", lambda row: None)
+    rows = news_enricher.build_analysis_rows(
+        symbol="AAPL",
+        news_rows=[
+            {"id": "news-1", "trade_date": "2026-03-10", "title": "Same title", "summary": "Same summary"},
+            {"id": "news-2", "trade_date": "2026-03-10", "title": "Same title", "summary": "Same summary"},
+        ],
+        ohlc_rows=[],
+    )
+    rows, stats = rows
+    assert len(rows) == 1
+    assert rows[0]["analysis_source"] == "llm"
+    assert rows[0]["summary"] == "Batch summary"
+    assert stats["deduped_count"] == 1
+    assert stats["llm_count"] == 1
+
+
+def test_enrich_news_for_symbol_skips_existing(monkeypatch):
+    class DummyStore:
+        def get_news_items(self, symbol, start_date=None, end_date=None, limit=200):
+            return [
+                {"id": "news-1", "trade_date": "2026-03-10", "title": "One", "summary": "One"},
+                {"id": "news-2", "trade_date": "2026-03-11", "title": "Two", "summary": "Two"},
+            ]
+
+        def get_analyzed_news_ids(self, symbol, start_date=None, end_date=None):
+            return {"news-1"}
+
+        def get_ohlc(self, symbol, start_date, end_date):
+            return []
+
+        def upsert_news_analysis(self, symbol, rows, analysis_source="local"):
+            self.rows = rows
+            return len(rows)
+
+    monkeypatch.setattr(
+        news_enricher,
+        "build_analysis_rows",
+        lambda symbol, news_rows, ohlc_rows: (
+            [
+                {
+                    "news_id": row["id"],
+                    "trade_date": row["trade_date"],
+                    "summary": row["summary"],
+                    "analysis_source": "local",
+                }
+                for row in news_rows
+            ],
+            {"deduped_count": 0, "llm_count": 0, "local_count": len(news_rows)},
+        ),
+    )
+    store = DummyStore()
+    result = news_enricher.enrich_news_for_symbol(store, "AAPL")
+    assert result["news_count"] == 2
+    assert result["queued_count"] == 1
+    assert result["skipped_existing_count"] == 1
+    assert len(store.rows) == 1
+    assert store.rows[0]["news_id"] == "news-2"
+
+
+def test_enrich_news_for_symbol_only_reanalyzes_local(monkeypatch):
+    class DummyStore:
+        def get_news_items(self, symbol, start_date=None, end_date=None, limit=200):
+            return [
+                {"id": "news-1", "trade_date": "2026-03-10", "title": "One", "summary": "One"},
+                {"id": "news-2", "trade_date": "2026-03-11", "title": "Two", "summary": "Two"},
+                {"id": "news-3", "trade_date": "2026-03-12", "title": "Three", "summary": "Three"},
+            ]
+
+        def get_analyzed_news_sources(self, symbol, start_date=None, end_date=None):
+            return {"news-1": "local", "news-2": "llm"}
+
+        def get_ohlc(self, symbol, start_date, end_date):
+            return []
+
+        def upsert_news_analysis(self, symbol, rows, analysis_source="local"):
+            self.rows = rows
+            return len(rows)
+
+    monkeypatch.setattr(
+        news_enricher,
+        "build_analysis_rows",
+        lambda symbol, news_rows, ohlc_rows: (
+            [
+                {
+                    "news_id": row["id"],
+                    "trade_date": row["trade_date"],
+                    "summary": row["summary"],
+                    "analysis_source": "llm" if row["id"] == "news-1" else "local",
+                }
+                for row in news_rows
+            ],
+            {"deduped_count": 0, "llm_count": 1, "local_count": 0},
+        ),
+    )
+
+    store = DummyStore()
+    result = news_enricher.enrich_news_for_symbol(
+        store,
+        "AAPL",
+        only_reanalyze_local=True,
+    )
+
+    assert result["news_count"] == 3
+    assert result["queued_count"] == 1
+    assert result["skipped_existing_count"] == 2
+    assert result["only_reanalyze_local"] is True
+    assert result["upgraded_local_to_llm_count"] == 1
+    assert result["execution_summary"]["upgraded_dates"] == ["2026-03-10"]
+    assert result["execution_summary"]["remaining_local_titles"] == []
+    assert result["execution_summary"]["skipped_missing_analysis_count"] == 1
+    assert result["execution_summary"]["skipped_non_local_count"] == 1
+    assert [row["news_id"] for row in store.rows] == ["news-1"]